Methods and systems for determination of boresight error in an optical system

ABSTRACT

Provided are methods for determination and correction of boresight shift caused by the installation of an optical layer over a camera assembly. Some methods described include performing a first calibration prior to installation of the window, performing a second calibration after installation of the window, and comparing the first and second calibrations to determine a transformation that corrects for the boresight shift. Systems and computer program products are also provided.

BACKGROUND

Covering a camera or other optical assembly with an additional layer,such as a protective layer, can cause a boresight shift. As used herein,the term boresight shift can refer to the misalignment of the camera orother optical assembly’s optical axis with a reference axis. Boresightshift can be caused by additional refraction or misalignment caused bythe optical properties of the additional layer.

BRIEF DESCRIPTION OF THE FIGURES

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1 is an example environment in which a vehicle including one ormore components of an autonomous system can be implemented;

FIG. 2 is a diagram of one or more systems of a vehicle including anautonomous system;

FIG. 3 is a diagram of components of one or more devices and/or one ormore systems of FIGS. 1 and 2 ;

FIG. 4 is a diagram of certain components of an autonomous system;

FIG. 5A illustrates an example of an autonomous system of a vehicleincluding one or more camera or other optical systems over an additionalprotective layer can be installed;

FIG. 5B illustrates an example of boresight shift caused by installationof an additional layer in front of a camera system.

FIG. 6 is a diagram of an implementation of a process for geometricintrinsic camera calibration using a diffractive optical element;

FIG. 7 is a diagram of an implementation of a geometric intrinsic cameracalibration system including a diffractive optical element;

FIGS. 8 and 9 are diagrams of implementations of diffractive opticalelements for geometric intrinsic camera calibration;

FIG. 10 is a flowchart of a process for manufacturing a geometricintrinsic camera calibration system including a diffractive opticalelement;

FIG. 11 is a further diagram of an implementation of a diffractiveoptical elements for geometric intrinsic camera calibration;

FIG. 12 is a flowchart of a process for geometric intrinsic cameracalibration using a diffractive optical element;

FIG. 13 is a flowchart of a further process for geometric intrinsiccamera calibration using a diffractive optical element;

FIG. 14 is a diagram showing an example image captured as part of aprocess for geometric intrinsic camera calibration using a diffractiveoptical element;

FIG. 15 is a diagram showing shapes identified in the sample image ofFIG. 14 as part of a process for geometric intrinsic camera calibrationusing a diffractive optical element;

FIG. 16 is a diagram showing a central shape identified in the image ofFIG. 15 as part of a process for geometric intrinsic camera calibrationusing a diffractive optical element;

FIG. 17 is a diagram showing the shapes of the image of FIG. 15 sortedinto an order as part of a process for geometric intrinsic cameracalibration using a diffractive optical element;

FIGS. 18A, 18B, and 18C illustrate different stages in determination andcorrection of boresight shift;

FIGS. 19A and 19B illustrate plots of pixel directions determined withand without a window installed over the camera assembly; and

FIG. 20 illustrates an embodiment of process for determining andcorrecting for boresight shift.

DETAILED DESCRIPTION

In the following description numerous specific details are set forth inorder to provide a thorough understanding of the present disclosure forthe purposes of explanation. It will be apparent, however, that theembodiments described by the present disclosure can be practiced withoutthese specific details. In some instances, well-known structures anddevices are illustrated in block diagram form in order to avoidunnecessarily obscuring aspects of the present disclosure.

Specific arrangements or orderings of schematic elements, such as thoserepresenting systems, devices, modules, instruction blocks, dataelements, and/or the like are illustrated in the drawings for ease ofdescription. However, it will be understood by those skilled in the artthat the specific ordering or arrangement of the schematic elements inthe drawings is not meant to imply that a particular order or sequenceof processing, or separation of processes, is required unless explicitlydescribed as such. Further, the inclusion of a schematic element in adrawing is not meant to imply that such element is required in allembodiments or that the features represented by such element may not beincluded in or combined with other elements in some embodiments unlessexplicitly described as such.

Further, where connecting elements such as solid or dashed lines orarrows are used in the drawings to illustrate a connection,relationship, or association between or among two or more otherschematic elements, the absence of any such connecting elements is notmeant to imply that no connection, relationship, or association canexist. In other words, some connections, relationships, or associationsbetween elements are not illustrated in the drawings so as not toobscure the disclosure. In addition, for ease of illustration, a singleconnecting element can be used to represent multiple connections,relationships or associations between elements. For example, where aconnecting element represents communication of signals, data, orinstructions (e.g., “software instructions”), it should be understood bythose skilled in the art that such element can represent one or multiplesignal paths (e.g., a bus), as may be needed, to affect thecommunication.

Although the terms first, second, third, and/or the like are used todescribe various elements, these elements should not be limited by theseterms. The terms first, second, third, and/or the like are used only todistinguish one element from another. For example, a first contact couldbe termed a second contact and, similarly, a second contact could betermed a first contact without departing from the scope of the describedembodiments. The first contact and the second contact are both contacts,but they are not the same contact.

The terminology used in the description of the various describedembodiments herein is included for the purpose of describing particularembodiments only and is not intended to be limiting. As used in thedescription of the various described embodiments and the appendedclaims, the singular forms “a,” “an” and “the” are intended to includethe plural forms as well and can be used interchangeably with “one ormore” or “at least one,” unless the context clearly indicates otherwise.It will also be understood that the term “and/or” as used herein refersto and encompasses any and all possible combinations of one or more ofthe associated listed items. It will be further understood that theterms “includes,” “including,” “comprises,” and/or “comprising,” whenused in this description specify the presence of stated features,integers, steps, operations, elements, and/or components, but do notpreclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof.

As used herein, the terms “communication” and “communicate” refer to atleast one of the reception, receipt, transmission, transfer, provision,and/or the like of information (or information represented by, forexample, data, signals, messages, instructions, commands, and/or thelike). For one unit (e.g., a device, a system, a component of a deviceor system, combinations thereof, and/or the like) to be in communicationwith another unit means that the one unit is able to directly orindirectly receive information from and/or send (e.g., transmit)information to the other unit. This may refer to a direct or indirectconnection that is wired and/or wireless in nature. Additionally, twounits may be in communication with each other even though theinformation transmitted may be modified, processed, relayed, and/orrouted between the first and second unit. For example, a first unit maybe in communication with a second unit even though the first unitpassively receives information and does not actively transmitinformation to the second unit. As another example, a first unit may bein communication with a second unit if at least one intermediary unit(e.g., a third unit located between the first unit and the second unit)processes information received from the first unit and transmits theprocessed information to the second unit. In some embodiments, a messagemay refer to a network packet (e.g., a data packet and/or the like) thatincludes data.

As used herein, the term “if” is, optionally, construed to mean “when”,“upon”, “in response to determining,” “in response to detecting,” and/orthe like, depending on the context. Similarly, the phrase “if it isdetermined” or “if [a stated condition or event] is detected” is,optionally, construed to mean “upon determining,” “in response todetermining,” “upon detecting [the stated condition or event],” “inresponse to detecting [the stated condition or event],” and/or the like,depending on the context. Also, as used herein, the terms “has”, “have”,“having”, or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based at least partially on”unless explicitly stated otherwise.

Reference will now be made in detail to embodiments, examples of whichare illustrated in the accompanying drawings. In the following detaileddescription, numerous specific details are set forth in order to providea thorough understanding of the various described embodiments. However,it will be apparent to one of ordinary skill in the art that the variousdescribed embodiments can be practiced without these specific details.In other instances, well-known methods, procedures, components,circuits, and networks have not been described in detail so as not tounnecessarily obscure aspects of the embodiments.

General Overview

In some aspects and/or embodiments, systems, methods, and computerprogram products described herein include and/or implement determinationand/or correction of boresight error in an optical system. For example,installation of a window over a camera assembly causes a boresight shiftthat misaligns the optical axis of the camera assembly with itsmechanical axis, leading to reduced performance of the camera assembly.For various reasons, including both aesthetic design reasons andfunctional reasons, it may be desirable to install a window over acamera assembly in an autonomous vehicle. A calibration processdescribed in this application can generate a transformation that can beused to compensate or correct for the boresight shift caused by thewindow. The calibration process comprises determining a first pluralityof pixel locations corresponding to a target prior to installation ofthe window, determining a second plurality of pixel locationscorresponding to the target subsequent to installation of the window,and generating a transformation that maps the second plurality of pixellocations to the first plurality of pixel locations. The transformationcan then be applied to subsequent images captured by the camera assemblyto correct or compensate for the boresight shift caused by the window.

By virtue of the implementation of systems, methods, and computerprogram products described herein, techniques for determination and/orcorrection of boresight error in an optical system provide a calibrationprocess that allows for correcting for boresight shift regardless of theoptical properties of the window, allowing for a wide variety of windowdesigns to be used without compromising the optical performance of thecamera assembly. In some instances, the calibration process reduces theprecision with which the windows must be installed relative to thecamera assemblies.

Referring now to FIG. 1 , illustrated is example environment 100 inwhich vehicles that include autonomous systems, as well as vehicles thatdo not, are operated. As illustrated, environment 100 includes vehicles102 a-102 n, objects 104 a-104 n, routes 106 a-106 n, area 108,vehicle-to-infrastructure (V2I) device 110, network 112, remoteautonomous vehicle (AV) system 114, fleet management system 116, and V2Isystem 118. Vehicles 102 a-102 n, vehicle-to-infrastructure (V2I) device110, network 112, autonomous vehicle (AV) system 114, fleet managementsystem 116, and V2I system 118 interconnect (e.g., establish aconnection to communicate and/or the like) via wired connections,wireless connections, or a combination of wired or wireless connections.In some embodiments, objects 104 a-104 n interconnect with at least oneof vehicles 102 a- 102 n, vehicle-to-infrastructure (V2I) device 110,network 112, autonomous vehicle (AV) system 114, fleet management system116, and V2I system 118 via wired connections, wireless connections, ora combination of wired or wireless connections.

Vehicles 102 a-102 n (referred to individually as vehicle 102 andcollectively as vehicles 102) include at least one device configured totransport goods and/or people. In some embodiments, vehicles 102 areconfigured to be in communication with V2I device 110, remote AV system114, fleet management system 116, and/or V2I system 118 via network 112.In some embodiments, vehicles 102 include cars, buses, trucks, trains,and/or the like. In some embodiments, vehicles 102 are the same as, orsimilar to, vehicles 200, described herein (see FIG. 2 ). In someembodiments, a vehicle 200 of a set of vehicles 200 is associated withan autonomous fleet manager. In some embodiments, vehicles 102 travelalong respective routes 106 a-106 n (referred to individually as route106 and collectively as routes 106), as described herein. In someembodiments, one or more vehicles 102 include an autonomous system(e.g., an autonomous system that is the same as or similar to autonomoussystem 202).

Objects 104 a-104 n (referred to individually as object 104 andcollectively as objects 104) include, for example, at least one vehicle,at least one pedestrian, at least one cyclist, at least one structure(e.g., a building, a sign, a fire hydrant, etc.), and/or the like. Eachobject 104 is stationary (e.g., located at a fixed location for a periodof time) or mobile (e.g., having a velocity and associated with at leastone trajectory). In some embodiments, objects 104 are associated withcorresponding locations in area 108.

Routes 106 a-106 n (referred to individually as route 106 andcollectively as routes 106) are each associated with (e.g., prescribe) asequence of actions (also known as a trajectory) connecting states alongwhich an AV can navigate. Each route 106 starts at an initial state(e.g., a state that corresponds to a first spatiotemporal location,velocity, and/or the like) and a final goal state (e.g., a state thatcorresponds to a second spatiotemporal location that is different fromthe first spatiotemporal location) or goal region (e.g. a subspace ofacceptable states (e.g., terminal states)). In some embodiments, thefirst state includes a location at which an individual or individualsare to be picked-up by the AV and the second state or region includes alocation or locations at which the individual or individuals picked-upby the AV are to be dropped-off. In some embodiments, routes 106 includea plurality of acceptable state sequences (e.g., a plurality ofspatiotemporal location sequences), the plurality of state sequencesassociated with (e.g., defining) a plurality of trajectories. In anexample, routes 106 include only high-level actions or imprecise statelocations, such as a series of connected roads dictating turningdirections at roadway intersections. Additionally, or alternatively,routes 106 may include more precise actions or states such as, forexample, specific target lanes or precise locations within the laneareas and targeted speed at those positions. In an example, routes 106include a plurality of precise state sequences along the at least onehigh level action sequence with a limited lookahead horizon to reachintermediate goals, where the combination of successive iterations oflimited horizon state sequences cumulatively correspond to a pluralityof trajectories that collectively form the high-level route to terminateat the final goal state or region.

Area 108 includes a physical area (e.g., a geographic region) withinwhich vehicles 102 can navigate. In an example, area 108 includes atleast one state (e.g., a country, a province, an individual state of aplurality of states included in a country, etc.), at least one portionof a state, at least one city, at least one portion of a city, etc. Insome embodiments, area 108 includes at least one named thoroughfare(referred to herein as a “road”) such as a highway, an interstatehighway, a parkway, a city street, etc. Additionally, or alternatively,in some examples area 108 includes at least one unnamed road such as adriveway, a section of a parking lot, a section of a vacant and/orundeveloped lot, a dirt path, etc. In some embodiments, a road includesat least one lane (e.g., a portion of the road that can be traversed byvehicles 102). In an example, a road includes at least one laneassociated with (e.g., identified based on) at least one lane marking.

Vehicle-to-Infrastructure (V2I) device 110 (sometimes referred to as aVehicle-to-Infrastructure (V2X) device) includes at least one deviceconfigured to be in communication with vehicles 102 and/or V2Iinfrastructure system 118. In some embodiments, V2I device 110 isconfigured to be in communication with vehicles 102, remote AV system114, fleet management system 116, and/or V2I system 118 via network 112.In some embodiments, V2I device 110 includes a radio frequencyidentification (RFID) device, signage, cameras (e.g., two-dimensional(2D) and/or three-dimensional (3D) cameras), lane markers, streetlights,parking meters, etc. In some embodiments, V2I device 110 is configuredto communicate directly with vehicles 102. Additionally, oralternatively, in some embodiments V2I device 110 is configured tocommunicate with vehicles 102, remote AV system 114, and/or fleetmanagement system 116 via V2I system 118. In some embodiments, V2Idevice 110 is configured to communicate with V2I system 118 via network112.

Network 112 includes one or more wired and/or wireless networks. In anexample, network 112 includes a cellular network (e.g., a long termevolution (LTE) network, a third generation (3G) network, a fourthgeneration (4G) network, a fifth generation (5G) network, a codedivision multiple access (CDMA) network, etc.), a public land mobilenetwork (PLMN), a local area network (LAN), a wide area network (WAN), ametropolitan area network (MAN), a telephone network (e.g., the publicswitched telephone network (PSTN), a private network, an ad hoc network,an intranet, the Internet, a fiber optic-based network, a cloudcomputing network, etc., a combination of some or all of these networks,and/or the like.

Remote AV system 114 includes at least one device configured to be incommunication with vehicles 102, V2I device 110, network 112, remote AVsystem 114, fleet management system 116, and/or V2I system 118 vianetwork 112. In an example, remote AV system 114 includes a server, agroup of servers, and/or other like devices. In some embodiments, remoteAV system 114 is co-located with the fleet management system 116. Insome embodiments, remote AV system 114 is involved in the installationof some or all of the components of a vehicle, including an autonomoussystem, an autonomous vehicle compute, software implemented by anautonomous vehicle compute, and/or the like. In some embodiments, remoteAV system 114 maintains (e.g., updates and/or replaces) such componentsand/or software during the lifetime of the vehicle.

Fleet management system 116 includes at least one device configured tobe in communication with vehicles 102, V2I device 110, remote AV system114, and/or V2I infrastructure system 118. In an example, fleetmanagement system 116 includes a server, a group of servers, and/orother like devices. In some embodiments, fleet management system 116 isassociated with a ridesharing company (e.g., an organization thatcontrols operation of multiple vehicles (e.g., vehicles that includeautonomous systems and/or vehicles that do not include autonomoussystems) and/or the like).

In some embodiments, V2I system 118 includes at least one deviceconfigured to be in communication with vehicles 102, V2I device 110,remote AV system 114, and/or fleet management system 116 via network112. In some examples, V2I system 118 is configured to be incommunication with V2I device 110 via a connection different fromnetwork 112. In some embodiments, V2I system 118 includes a server, agroup of servers, and/or other like devices. In some embodiments, V2Isystem 118 is associated with a municipality or a private institution(e.g., a private institution that maintains V2I device 110 and/or thelike).

The number and arrangement of elements illustrated in FIG. 1 areprovided as an example. There can be additional elements, fewerelements, different elements, and/or differently arranged elements, thanthose illustrated in FIG. 1 . Additionally, or alternatively, at leastone element of environment 100 can perform one or more functionsdescribed as being performed by at least one different element of FIG. 1. Additionally, or alternatively, at least one set of elements ofenvironment 100 can perform one or more functions described as beingperformed by at least one different set of elements of environment 100.

Referring now to FIG. 2 , vehicle 200 includes autonomous system 202,powertrain control system 204, steering control system 206, and brakesystem 208. In some embodiments, vehicle 200 is the same as or similarto vehicle 102 (see FIG. 1 ). In some embodiments, vehicle 102 haveautonomous capability (e.g., implement at least one function, feature,device, and/or the like that enable vehicle 200 to be partially or fullyoperated without human intervention including, without limitation, fullyautonomous vehicles (e.g., vehicles that forego reliance on humanintervention), highly autonomous vehicles (e.g., vehicles that foregoreliance on human intervention in certain situations), and/or the like).For a detailed description of fully autonomous vehicles and highlyautonomous vehicles, reference may be made to SAE International’sstandard J3016: Taxonomy and Definitions for Terms Related to On-RoadMotor Vehicle Automated Driving Systems, which is incorporated byreference in its entirety. In some embodiments, vehicle 200 isassociated with an autonomous fleet manager and/or a ridesharingcompany.

Autonomous system 202 includes a sensor suite that includes one or moredevices such as cameras 202 a, LiDAR sensors 202 b, radar sensors 202 c,and microphones 202 d. In some embodiments, autonomous system 202 caninclude more or fewer devices and/or different devices (e.g., ultrasonicsensors, inertial sensors, GPS receivers (discussed below), odometrysensors that generate data associated with an indication of a distancethat vehicle 200 has traveled, and/or the like). In some embodiments,autonomous system 202 uses the one or more devices included inautonomous system 202 to generate data associated with environment 100,described herein. The data generated by the one or more devices ofautonomous system 202 can be used by one or more systems describedherein to observe the environment (e.g., environment 100) in whichvehicle 200 is located. In some embodiments, autonomous system 202includes communication device 202 e, autonomous vehicle compute 202 f,and drive-by-wire (DBW) system 202 h.

Cameras 202 a include at least one device configured to be incommunication with communication device 202 e, autonomous vehiclecompute 202 f, and/or safety controller 202 g via a bus (e.g., a busthat is the same as or similar to bus 302 of FIG. 3 ). Cameras 202 ainclude at least one camera (e.g., a digital camera using a light sensorsuch as a charge-coupled device (CCD), a thermal camera, an infrared(IR) camera, an event camera, and/or the like) to capture imagesincluding physical objects (e.g., cars, buses, curbs, people, and/or thelike). In some embodiments, camera 202 a generates camera data asoutput. In some examples, camera 202 a generates camera data thatincludes image data associated with an image. In this example, the imagedata may specify at least one parameter (e.g., image characteristicssuch as exposure, brightness, etc., an image timestamp, and/or the like)corresponding to the image. In such an example, the image may be in aformat (e.g., RAW, JPEG, PNG, and/or the like). In some embodiments,camera 202 a includes a plurality of independent cameras configured on(e.g., positioned on) a vehicle to capture images for the purpose ofstereopsis (stereo vision). In some examples, camera 202 a includes aplurality of cameras that generate image data and transmit the imagedata to autonomous vehicle compute 202 f and/or a fleet managementsystem (e.g., a fleet management system that is the same as or similarto fleet management system 116 of FIG. 1 ). In such an example,autonomous vehicle compute 202 f determines depth to one or more objectsin a field of view of at least two cameras of the plurality of camerasbased on the image data from the at least two cameras. In someembodiments, cameras 202 a is configured to capture images of objectswithin a distance from cameras 202 a (e.g., up to 100 meters, up to akilometer, and/or the like). Accordingly, cameras 202 a include featuressuch as sensors and lenses that are optimized for perceiving objectsthat are at one or more distances from cameras 202 a.

In an embodiment, camera 202 a includes at least one camera configuredto capture one or more images associated with one or more trafficlights, street signs and/or other physical objects that provide visualnavigation information. In some embodiments, camera 202 a generatestraffic light data associated with one or more images. In some examples,camera 202 a generates TLD data associated with one or more images thatinclude a format (e.g., RAW, JPEG, PNG, and/or the like). In someembodiments, camera 202 a that generates TLD data differs from othersystems described herein incorporating cameras in that camera 202 a caninclude one or more cameras with a wide field of view (e.g., awide-angle lens, a fish-eye lens, a lens having a viewing angle ofapproximately 120 degrees or more, and/or the like) to generate imagesabout as many physical objects as possible.

Laser Detection and Ranging (LiDAR) sensors 202 b include at least onedevice configured to be in communication with communication device 202e, autonomous vehicle compute 202 f, and/or safety controller 202 g viaa bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). LiDAR sensors 202 b include a system configured to transmit lightfrom a light emitter (e.g., a laser transmitter). Light emitted by LiDARsensors 202 b include light (e.g., infrared light and/or the like) thatis outside of the visible spectrum. In some embodiments, duringoperation, light emitted by LiDAR sensors 202 b encounters a physicalobject (e.g., a vehicle) and is reflected back to LiDAR sensors 202 b.In some embodiments, the light emitted by LiDAR sensors 202 b does notpenetrate the physical objects that the light encounters. LiDAR sensors202 b also include at least one light detector which detects the lightthat was emitted from the light emitter after the light encounters aphysical object. In some embodiments, at least one data processingsystem associated with LiDAR sensors 202 b generates an image (e.g., apoint cloud, a combined point cloud, and/or the like) representing theobjects included in a field of view of LiDAR sensors 202 b. In someexamples, the at least one data processing system associated with LiDARsensor 202 b generates an image that represents the boundaries of aphysical object, the surfaces (e.g., the topology of the surfaces) ofthe physical object, and/or the like. In such an example, the image isused to determine the boundaries of physical objects in the field ofview of LiDAR sensors 202 b.

Radio Detection and Ranging (radar) sensors 202 c include at least onedevice configured to be in communication with communication device 202e, autonomous vehicle compute 202 f, and/or safety controller 202 g viaa bus (e.g., a bus that is the same as or similar to bus 302 of FIG. 3). Radar sensors 202 c include a system configured to transmit radiowaves (either pulsed or continuously). The radio waves transmitted byradar sensors 202 c include radio waves that are within a predeterminedspectrum In some embodiments, during operation, radio waves transmittedby radar sensors 202 c encounter a physical object and are reflectedback to radar sensors 202 c. In some embodiments, the radio wavestransmitted by radar sensors 202 c are not reflected by some objects. Insome embodiments, at least one data processing system associated withradar sensors 202 c generates signals representing the objects includedin a field of view of radar sensors 202 c. For example, the at least onedata processing system associated with radar sensor 202 c generates animage that represents the boundaries of a physical object, the surfaces(e.g., the topology of the surfaces) of the physical object, and/or thelike. In some examples, the image is used to determine the boundaries ofphysical objects in the field of view of radar sensors 202 c.

Microphones 202 d includes at least one device configured to be incommunication with communication device 202 e, autonomous vehiclecompute 202 f, and/or safety controller 202 g via a bus (e.g., a busthat is the same as or similar to bus 302 of FIG. 3 ). Microphones 202 dinclude one or more microphones (e.g., array microphones, externalmicrophones, and/or the like) that capture audio signals and generatedata associated with (e.g., representing) the audio signals. In someexamples, microphones 202 d include transducer devices and/or likedevices. In some embodiments, one or more systems described herein canreceive the data generated by microphones 202 d and determine a positionof an object relative to vehicle 200 (e.g., a distance and/or the like)based on the audio signals associated with the data.

Communication device 202 e include at least one device configured to bein communication with cameras 202 a, LiDAR sensors 202 b, radar sensors202 c, microphones 202 d, autonomous vehicle compute 202 f, safetycontroller 202 g, and/or DBW system 202 h. For example, communicationdevice 202 e may include a device that is the same as or similar tocommunication interface 314 of FIG. 3 . In some embodiments,communication device 202 e includes a vehicle-to-vehicle (V2V)communication device (e.g., a device that enables wireless communicationof data between vehicles).

Autonomous vehicle compute 202 f include at least one device configuredto be in communication with cameras 202 a, LiDAR sensors 202 b, radarsensors 202 c, microphones 202 d, communication device 202 e, safetycontroller 202 g, and/or DBW system 202 h. In some examples, autonomousvehicle compute 202 f includes a device such as a client device, amobile device (e.g., a cellular telephone, a tablet, and/or the like) aserver (e.g., a computing device including one or more centralprocessing units, graphical processing units, and/or the like), and/orthe like. In some embodiments, autonomous vehicle compute 202 f is thesame as or similar to autonomous vehicle compute 400, described herein.Additionally, or alternatively, in some embodiments autonomous vehiclecompute 202 f is configured to be in communication with an autonomousvehicle system (e.g., an autonomous vehicle system that is the same asor similar to remote AV system 114 of FIG. 1 ), a fleet managementsystem (e.g., a fleet management system that is the same as or similarto fleet management system 116 of FIG. 1 ), a V2I device (e.g., a V2Idevice that is the same as or similar to V2I device 110 of FIG. 1 ),and/or a V2I system (e.g., a V2I system that is the same as or similarto V2I system 118 of FIG. 1 ).

Safety controller 202 g includes at least one device configured to be incommunication with cameras 202 a, LiDAR sensors 202 b, radar sensors 202c, microphones 202 d, communication device 202 e, autonomous vehiclecomputer 202 f, and/or DBW system 202 h. In some examples, safetycontroller 202 g includes one or more controllers (electricalcontrollers, electromechanical controllers, and/or the like) that areconfigured to generate and/or transmit control signals to operate one ormore devices of vehicle 200 (e.g., powertrain control system 204,steering control system 206, brake system 208, and/or the like). In someembodiments, safety controller 202 g is configured to generate controlsignals that take precedence over (e.g., overrides) control signalsgenerated and/or transmitted by autonomous vehicle compute 202 f.

DBW system 202 h includes at least one device configured to be incommunication with communication device 202 e and/or autonomous vehiclecompute 202 f. In some examples, DBW system 202 h includes one or morecontrollers (e.g., electrical controllers, electromechanicalcontrollers, and/or the like) that are configured to generate and/ortransmit control signals to operate one or more devices of vehicle 200(e.g., powertrain control system 204, steering control system 206, brakesystem 208, and/or the like). Additionally, or alternatively, the one ormore controllers of DBW system 202 h are configured to generate and/ortransmit control signals to operate at least one different device (e.g.,a turn signal, headlights, door locks, windshield wipers, and/or thelike) of vehicle 200.

Powertrain control system 204 includes at least one device configured tobe in communication with DBW system 202 h. In some examples, powertraincontrol system 204 includes at least one controller, actuator, and/orthe like. In some embodiments, powertrain control system 204 receivescontrol signals from DBW system 202 h and powertrain control system 204causes vehicle 200 to start moving forward, stop moving forward, startmoving backward, stop moving backward, accelerate in a direction,decelerate in a direction, perform a left turn, perform a right turn,and/or the like. In an example, powertrain control system 204 causes theenergy (e.g., fuel, electricity, and/or the like) provided to a motor ofthe vehicle to increase, remain the same, or decrease, thereby causingat least one wheel of vehicle 200 to rotate or not rotate.

Steering control system 206 includes at least one device configured torotate one or more wheels of vehicle 200. In some examples, steeringcontrol system 206 includes at least one controller, actuator, and/orthe like. In some embodiments, steering control system 206 causes thefront two wheels and/or the rear two wheels of vehicle 200 to rotate tothe left or right to cause vehicle 200 to turn to the left or right.

Brake system 208 includes at least one device configured to actuate oneor more brakes to cause vehicle 200 to reduce speed and/or remainstationary. In some examples, brake system 208 includes at least onecontroller and/or actuator that is configured to cause one or morecalipers associated with one or more wheels of vehicle 200 to close on acorresponding rotor of vehicle 200. Additionally, or alternatively, insome examples brake system 208 includes an automatic emergency braking(AEB) system, a regenerative braking system, and/or the like.

In some embodiments, vehicle 200 includes at least one platform sensor(not explicitly illustrated) that measures or infers properties of astate or a condition of vehicle 200. In some examples, vehicle 200includes platform sensors such as a global positioning system (GPS)receiver, an inertial measurement unit (IMU), a wheel speed sensor, awheel brake pressure sensor, a wheel torque sensor, an engine torquesensor, a steering angle sensor, and/or the like.

Referring now to FIG. 3 , illustrated is a schematic diagram of a device300. As illustrated, device 300 includes processor 304, memory 306,storage component 308, input interface 310, output interface 312,communication interface 314, and bus 302. In some embodiments, device300 corresponds to at least one device of vehicles 102 (e.g., at leastone device of a system of vehicles 102), at least one device vehicles200, and/or one or more devices of network 112 (e.g., one or moredevices of a system of network 112). In some embodiments, one or moredevices of vehicles 102 (e.g., one or more devices of a system ofvehicles 102), one or more devices of vehicle 200, and/or one or moredevices of network 112 (e.g., one or more devices of a system of network112) include at least one device 300 and/or at least one component ofdevice 300. As shown in FIG. 3 , device 300 includes bus 302, processor304, memory 306, storage component 308, input interface 310, outputinterface 312, and communication interface 314.

Bus 302 includes a component that permits communication among thecomponents of device 300. In some embodiments, processor 304 isimplemented in hardware, software, or a combination of hardware andsoftware. In some examples, processor 304 includes a processor (e.g., acentral processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), and/or the like), a microphone, adigital signal processor (DSP), and/or any processing component (e.g., afield-programmable gate array (FPGA), an application specific integratedcircuit (ASIC), and/or the like) that can be programmed to perform atleast one function. Memory 306 includes random access memory (RAM),read-only memory (ROM), and/or another type of dynamic and/or staticstorage device (e.g., flash memory, magnetic memory, optical memory,and/or the like) that stores data and/or instructions for use byprocessor 304.

Storage component 308 stores data and/or software related to theoperation and use of device 300. In some examples, storage component 308includes a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, a solid-state disk, and/or the like), a compact disc(CD), a digital versatile disc (DVD), a floppy disk, a cartridge, amagnetic tape, a CD-ROM, RAM, PROM, EPROM, FLASH-EPROM, NV-RAM, and/oranother type of computer readable medium, along with a correspondingdrive.

Input interface 310 includes a component that permits device 300 toreceive information, such as via user input (e.g., a touchscreendisplay, a keyboard, a keypad, a mouse, a button, a switch, amicrophone, a camera, and/or the like). Additionally or alternatively,in some embodiments input interface 310 includes a sensor that sensesinformation (e.g., a global positioning system (GPS) receiver, anaccelerometer, a gyroscope, an actuator, and/or the like). Outputinterface 312 includes a component that provides output information fromdevice 300 (e.g., a display, a speaker, one or more light-emittingdiodes (LEDs), and/or the like).

In some embodiments, communication interface 314 includes atransceiver-like component (e.g., a transceiver, a separate receiver andtransmitter, and/or the like) that permits device 300 to communicatewith other devices via a wired connection, a wireless connection, or acombination of wired and wireless connections. In some examples,communication interface 314 permits device 300 to receive informationfrom another device and/or provide information to another device. Insome examples, communication interface 314 includes an Ethernetinterface, an optical interface, a coaxial interface, an infraredinterface, a radio frequency (RF) interface, a universal serial bus(USB) interface, a Wi-Fi® interface, a cellular network interface,and/or the like.

In some embodiments, device 300 performs one or more processes describedherein. Device 300 performs these processes based on processor 304executing software instructions stored by a computer-readable medium,such as memory 305 and/or storage component 308. A computer-readablemedium (e.g., a non-transitory computer readable medium) is definedherein as a non-transitory memory device. A non-transitory memory deviceincludes memory space located inside a single physical storage device ormemory space spread across multiple physical storage devices.

In some embodiments, software instructions are read into memory 306and/or storage component 308 from another computer-readable medium orfrom another device via communication interface 314. When executed,software instructions stored in memory 306 and/or storage component 308cause processor 304 to perform one or more processes described herein.Additionally or alternatively, hardwired circuitry is used in place ofor in combination with software instructions to perform one or moreprocesses described herein. Thus, embodiments described herein are notlimited to any specific combination of hardware circuitry and softwareunless explicitly stated otherwise.

Memory 306 and/or storage component 308 includes data storage or atleast one data structure (e.g., a database and/or the like). Device 300is capable of receiving information from, storing information in,communicating information to, or searching information stored in thedata storage or the at least one data structure in memory 306 or storagecomponent 308. In some examples, the information includes network data,input data, output data, or any combination thereof.

In some embodiments, device 300 is configured to execute softwareinstructions that are either stored in memory 306 and/or in the memoryof another device (e.g., another device that is the same as or similarto device 300). As used herein, the term “module” refers to at least oneinstruction stored in memory 306 and/or in the memory of another devicethat, when executed by processor 304 and/or by a processor of anotherdevice (e.g., another device that is the same as or similar to device300) cause device 300 (e.g., at least one component of device 300) toperform one or more processes described herein. In some embodiments, amodule is implemented in software, firmware, hardware, and/or the like.

The number and arrangement of components illustrated in FIG. 3 areprovided as an example. In some embodiments, device 300 can includeadditional components, fewer components, different components, ordifferently arranged components than those illustrated in FIG. 3 .Additionally or alternatively, a set of components (e.g., one or morecomponents) of device 300 can perform one or more functions described asbeing performed by another component or another set of components ofdevice 300.

Referring now to FIG. 4 , illustrated is an example block diagram of anautonomous vehicle compute 400 (sometimes referred to as an “AV stack”).As illustrated, autonomous vehicle compute 400 includes perceptionsystem 402 (sometimes referred to as a perception module), planningsystem 404 (sometimes referred to as a planning module), localizationsystem 406 (sometimes referred to as a localization module), controlsystem 408 (sometimes referred to as a control module), and database410. In some embodiments, perception system 402, planning system 404,localization system 406, control system 408, and database 410 areincluded and/or implemented in an autonomous navigation system of avehicle (e.g., autonomous vehicle compute 202 f of vehicle 200).Additionally, or alternatively, in some embodiments perception system402, planning system 404, localization system 406, control system 408,and database 410 are included in one or more standalone systems (e.g.,one or more systems that are the same as or similar to autonomousvehicle compute 400 and/or the like). In some examples, perceptionsystem 402, planning system 404, localization system 406, control system408, and database 410 are included in one or more standalone systemsthat are located in a vehicle and/or at least one remote system asdescribed herein. In some embodiments, any and/or all of the systemsincluded in autonomous vehicle compute 400 are implemented in software(e.g., in software instructions stored in memory), computer hardware(e.g., by microprocessors, microcontrollers, application-specificintegrated circuits [ASICs], Field Programmable Gate Arrays (FPGAs),and/or the like), or combinations of computer software and computerhardware. It will also be understood that, in some embodiments,autonomous vehicle compute 400 is configured to be in communication witha remote system (e.g., an autonomous vehicle system that is the same asor similar to remote AV system 114, a fleet management system 116 thatis the same as or similar to fleet management system 116, a V2I systemthat is the same as or similar to V2I system 118, and/or the like).

In some embodiments, perception system 402 receives data associated withat least one physical object (e.g., data that is used by perceptionsystem 402 to detect the at least one physical object) in an environmentand classifies the at least one physical object. In some examples,perception system 402 receives image data captured by at least onecamera (e.g., cameras 202 a), the image associated with (e.g.,representing) one or more physical objects within a field of view of theat least one camera. In such an example, perception system 402classifies at least one physical object based on one or more groupingsof physical objects (e.g., bicycles, vehicles, traffic signs,pedestrians, and/or the like). In some embodiments, perception system402 transmits data associated with the classification of the physicalobjects to planning system 404 based on perception system 402classifying the physical objects.

In some embodiments, planning system 404 receives data associated with adestination and generates data associated with at least one route (e.g.,routes 106) along which a vehicle (e.g., vehicles 102) can travel alongtoward a destination. In some embodiments, planning system 404periodically or continuously receives data from perception system 402(e.g., data associated with the classification of physical objects,described above) and planning system 404 updates the at least onetrajectory or generates at least one different trajectory based on thedata generated by perception system 402. In some embodiments, planningsystem 404 receives data associated with an updated position of avehicle (e.g., vehicles 102) from localization system 406 and planningsystem 404 updates the at least one trajectory or generates at least onedifferent trajectory based on the data generated by localization system406.

In some embodiments, localization system 406 receives data associatedwith (e.g., representing) a location of a vehicle (e.g., vehicles 102)in an area. In some examples, localization system 406 receives LiDARdata associated with at least one point cloud generated by at least oneLiDAR sensor (e.g., LiDAR sensors 202 b). In certain examples,localization system 406 receives data associated with at least one pointcloud from multiple LiDAR sensors and localization system 406 generatesa combined point cloud based on each of the point clouds. In theseexamples, localization system 406 compares the at least one point cloudor the combined point cloud to two-dimensional (2D) and/or athree-dimensional (3D) map of the area stored in database 410.Localization system 406 then determines the position of the vehicle inthe area based on localization system 406 comparing the at least onepoint cloud or the combined point cloud to the map. In some embodiments,the map includes a combined point cloud of the area generated prior tonavigation of the vehicle. In some embodiments, maps include, withoutlimitation, high-precision maps of the roadway geometric properties,maps describing road network connectivity properties, maps describingroadway physical properties (such as traffic speed, traffic volume, thenumber of vehicular and cyclist traffic lanes, lane width, lane trafficdirections, or lane marker types and locations, or combinationsthereof), and maps describing the spatial locations of road featuressuch as crosswalks, traffic signs or other travel signals of varioustypes. In some embodiments, the map is generated in real-time based onthe data received by the perception system.

In another example, localization system 406 receives Global NavigationSatellite System (GNSS) data generated by a global positioning system(GPS) receiver. In some examples, localization system 406 receives GNSSdata associated with the location of the vehicle in the area andlocalization system 406 determines a latitude and longitude of thevehicle in the area. In such an example, localization system 406determines the position of the vehicle in the area based on the latitudeand longitude of the vehicle. In some embodiments, localization system406 generates data associated with the position of the vehicle. In someexamples, localization system 406 generates data associated with theposition of the vehicle based on localization system 406 determining theposition of the vehicle. In such an example, the data associated withthe position of the vehicle includes data associated with one or moresemantic properties corresponding to the position of the vehicle.

In some embodiments, control system 408 receives data associated with atleast one trajectory from planning system 404 and control system 408controls operation of the vehicle. In some examples, control system 408receives data associated with at least one trajectory from planningsystem 404 and control system 408 controls operation of the vehicle bygenerating and transmitting control signals to cause a powertraincontrol system (e.g., DBW system 202 h, powertrain control system 204,and/or the like), a steering control system (e.g., steering controlsystem 206), and/or a brake system (e.g., brake system 208) to operate.In an example, where a trajectory includes a left turn, control system408 transmits a control signal to cause steering control system 206 toadjust a steering angle of vehicle 200, thereby causing vehicle 200 toturn left. Additionally, or alternatively, control system 408 generatesand transmits control signals to cause other devices (e.g., headlights,turn signal, door locks, windshield wipers, and/or the like) of vehicle200 to change states.

In some embodiments, perception system 402, planning system 404,localization system 406, and/or control system 408 implement at leastone machine learning model (e.g., at least one multilayer perceptron(MLP), at least one convolutional neural network (CNN), at least onerecurrent neural network (RNN), at least one autoencoder, at least onetransformer, and/or the like). In some examples, perception system 402,planning system 404, localization system 406, and/or control system 408implement at least one machine learning model alone or in combinationwith one or more of the above-noted systems. In some examples,perception system 402, planning system 404, localization system 406,and/or control system 408 implement at least one machine learning modelas part of a pipeline (e.g., a pipeline for identifying one or moreobjects located in an environment and/or the like).

Database 410 stores data that is transmitted to, received from, and/orupdated by perception system 402, planning system 404, localizationsystem 406 and/or control system 408. In some examples, database 410includes a storage component (e.g., a storage component that is the sameas or similar to storage component 308 of FIG. 3 ) that stores dataand/or software related to the operation and uses at least one system ofautonomous vehicle compute 400. In some embodiments, database 410 storesdata associated with 2D and/or 3D maps of at least one area. In someexamples, database 410 stores data associated with 2D and/or 3D maps ofa portion of a city, multiple portions of multiple cities, multiplecities, a county, a state, a State (e.g., a country), and/or the like).In such an example, a vehicle (e.g., a vehicle that is the same as orsimilar to vehicles 102 and/or vehicle 200) can drive along one or moredrivable regions (e.g., single-lane roads, multi-lane roads, highways,back roads, off road trails, and/or the like) and cause at least oneLiDAR sensor (e.g., a LiDAR sensor that is the same as or similar toLiDAR sensors 202 b) to generate data associated with an imagerepresenting the objects included in a field of view of the at least oneLiDAR sensor.

In some embodiments, database 410 can be implemented across a pluralityof devices. In some examples, database 410 is included in a vehicle(e.g., a vehicle that is the same as or similar to vehicles 102 and/orvehicle 200), an autonomous vehicle system (e.g., an autonomous vehiclesystem that is the same as or similar to remote AV system 114, a fleetmanagement system (e.g., a fleet management system that is the same asor similar to fleet management system 116 of FIG. 1 , a V2I system(e.g., a V2I system that is the same as or similar to V2I system 118 ofFIG. 1 ) and/or the like.

As described above, autonomous systems, such as those described withrespect to FIGS. 1-4 , can rely on the input of, among other things, oneor more optical or camera systems or assemblies. For example, theautonomous systems 202 of the vehicle 200 includes cameras 202 adescribed above. FIG. 5A illustrates an embodiment of an autonomoussystem 500 that can be included on a vehicle. As shown in FIG. 5A, thesystem 500 can include one or more camera or other optical assemblies502 positioned thereon. The one or more camera or other opticalassemblies 502 can include lens and image sensors that gather imagesthat can be used by the autonomous system 500 to facilitate driving ofthe vehicle.

In some instances, it may be desirable to cover the camera or otheroptical assemblies 502 with a window. For example, a window can beinstalled over any of the optical assemblies 502 shown in FIG. 5A, orany other optical assembly. A window may be installed to protect theoptical assembly from, for example, impact, dust, water, etc. In someembodiments, the window may be installed for stylistic reasons (e.g., toimprove the aesthetics of the vehicle). Additionally or alternatively,the window may improve the functionality of the sensor. For example, thewindow may provide athermazaliation, moisture mitigation, intrinsicthermal shift testing using thermal chamber, a hydrophobic coatingrequirements, or other types of functionality. In some embodiments, thewindow may comprise a clear layer and can be formed from a material suchas additional layer of glass, silica, polycarbonate, or other materials.

Installation of a window over the optical sensors 502, however, cancause some problems. For example, installation of a window over anoptical sensor can cause a boresight shift. A boresight shift can referto the misalignment of an optical system’s axis relative to with acertain reference optical axis or mechanical axis. For example, when theoptical sensors 502 are installed, they are generally installed at acertain position such that the optical axis of the optical sensors 502are pointed in desirable directions. Installing a window over theoptical sensors 502 causes a shift that misaligns the optical sensors502 with their desirable orientation. In particular, a shift in pixelsis caused when an optical layer is added to the camera system due to theadded refraction and misalignment caused by this new material. Thischanges the intrinsic characteristics of the camera system, which if notaccounted for, can lead to reduced performance and accuracy for anautonomous system that relies on the optical sensors 502 as an input.Accordingly, it can be beneficial to determine the degree of theboresight shift caused by the new material and correct for it.

This application provides methods and systems for computing andvisualizing the boresight aberration in an optical system. As will bediscussed in more detail, intrinsic parameters of the optical systemwith and without the added window are determined and compared todetermine the different directions in which the pixels point as causedby the window. In some embodiments, the methodology includes creating agrid of pixel locations covering the calibrated field of view in bothcases (e.g., with and without the window installed). For each pixelwithin the grid, the direction (e.g., the three-dimensional raydirection) of the pixel is determined based on an intrinsic calibrationof the camera. The angular error between directions with and without thewindow installed can then be determined. This angular error representsthe boresight shift. In some embodiments, the angular error isdetermined in arcmins. This error can be represented as a quiver plot. Atransformation between the differences can be generated and applied tocorrect for the boresight shift. In some instances, once this error iscalculated, it may not be necessary to align the optical layer or windowperfectly. This can be because a transformation can be computed thatcorrects for errors caused by the alignment of the window. For example,once the rotation and translation matrix is determined, the system isnot susceptible to alignment issues. Additionally, the capability tomeasure and correct for the boresight shift also aids with the usage andselection of a variety of materials irrespective of the materialsrefractive index or different curvature.

FIG. 5B schematically illustrates an example of boresight shift causedby installation of a window 504 over a camera assembly 502, whichcomprise a lens module 506 and an image sensor 508. As shown in thisexample, the window 504 is installed in front of the lends module 508such that rays of light pass through the window 504 prior to passingthrough the lens module 506 to ultimately be focused onto the imagesensor 508. For comparison, the rays are illustrated both as affected bythe window 504 and as if the window 504 was not present. Additionally,rays are illustrated at both an on-axis position (the center raysillustrated in blue) and two off axis positions above (+7.8 degrees FOV)and below (-7.8 degrees FOV) the on-axis position (as illustrated in red(above) and green (below). For each ray, a certain amount of diffractionoccurs as the rays pass through the window. For objects appearing at 150yards, this diffraction can lead to a significant shift in the perceivedlocation of the object. For example, for the on-axis ray, a shift of.427 meters occurs. Even more extreme, at the off-axis positions, shiftsof 2.8 meters and 6.6 meters occur. While these examples relate to aspecific configuration and orientation of the window, the problemsassociated with boresight shift are illustrated clearly. If notaccounted for, objects may appear shifted from their actual location,which can be particularly problematic in autonomous systems that rely onthe output of the camera assembly 502 to determine how to guide avehicle.

Determining the boresight shift and correcting for it can beaccomplished by comparing the differences in the intrinsic parameters ofthe camera system both with and without the window installed. One methodfor determining the intrinsic parameters of the camera can include theuse of a diffractive optical element (DOE). FIGS. 6-17 illustrateexamples of a DOE intrinsic calibration module according to oneembodiment, as well as associated methods of manufacture and use of thesame. As will be described further below, such a DOE intrinsiccalibration module can be utilized during a boresight shiftdetermination and correction process.

Referring now to FIG. 6 , illustrated is a diagram of an implementationof a process 600 for geometric intrinsic camera calibration using adiffractive optical element. In some embodiments, one or more of thesteps described with respect to process 600 are performed (e.g.,completely, partially, and/or the like) by autonomous vehicle 102, asabove. Additionally or alternatively, in some embodiments one or moresteps described with respect to process 600 may be performed (e.g.,completely, partially, and/or the like) by another device or group ofdevices separate from or including autonomous vehicle 102, such as aremote server (e.g., a remote server that is the same as or similar toremote AV system 114 and/or fleet management system 116 of FIG. 1 )carrying out some or all of the above calculations.

As shown in FIG. 6 , a device 602 including a diffractive opticalelement 604 is aligned with an optical axis of a camera 202 a (e.g.,which may be affixed to autonomous vehicle 102 in some examples). Device602 projects light beams 604 upon camera 202 a via the diffractiveoptical element 604. Each of light beams 604 has a propagation directionassociated with a corresponding view angle from among multiple viewangles of camera 202 a. Camera 202 a captures an image 606 based onlight beams 604 and forward the image to one or more processors 608 viadata port 610. Processor 608 executes instructions stored in memory 612to identify (614) shapes in the received image 606, determine (616) acorrespondence between the shapes in the image 606 and the light beams604, compute (618) pixel coordinates for the shapes, store (620) a tableassociating the pixel coordinates with corresponding propagationdirections of the light beams 604, and identify (622) one or moreintrinsic parameters of the camera that minimize a reprojection errorfunction based on the shapes in the image 606 and the propagationdirections.

Referring now to FIG. 7 , illustrated is a diagram of an implementationof a geometric intrinsic camera calibration system 700. In someembodiments, system 700 includes a laser 702 (e.g., a solid-statelaser), a beam expanding lens 704, a collimator 706, a diffractiveoptical element 708 (which, for example, may be the same as, or similarto, one or more diffractive optical element(s) described elsewhereherein), and a protective window 712. Laser 702 is configured to outputa first light beam 712 toward collimator 706, optionally by way of beamexpanding lens 704. In some examples, beam expanding lens 704 isconfigured to expand the first light beam 712 into an expanded lightbeam 714 and provide the expanded light beam to collimator 706. In stillother examples, collimator 706 is a beam expanding type of collimatorthat is configured to expand the first light beam 712 output by thelaser 702, thereby causing a diameter of the collimated light beam 716to be greater than a diameter of the first light beam 712 output by thelaser 702. Collimator 706 is arranged along an optical path of laser 702and is configured to output a collimated light beam 716 based on thefirst light beam 712 (or the expanded light beam 714, as the case maybe) received from laser 702 (and/or beam expanding lens 704).

Diffractive optical element 708 is arranged along an optical path ofcollimator 706 and includes a first surface 718 and a second surface720. First surface 718 (e.g., a flat side) includes a mask (notseparately shown in FIG. 7 ) having apertures corresponding to viewangles of a camera (e.g., camera 202 a, not separately shown in FIG. 7). Second surface 720 includes ridges (not separately shown in FIG. 7 )corresponding to the view angles, each ridge having a ridge angleassociated with the corresponding view angle. Diffractive opticalelement 708 is configured to split the collimated light beam 716 intomultiple light beams 722 by passing the collimated light beam 716through apertures (e.g., such as apertures 808 shown in FIG. 8 ), andoutput the light beams 722 through the ridges to a lens (not separatelyshown in FIG. 7 ) of the camera for calibration, the light beams 722being output in respective propagation directions based on the ridgeangles. In one example, the light beams 722 are configured during adesign phase of the DOE 708. In such an example, a grating angle of theDOE 708 is predetermined based on a desired number of light beams (e.g.,light beams 722) in which the primary light beam 712 is to be split, forinstance, by utilizing equations (1), (2), and (3) in the mannerdescribed below. In another example, various aspects of the DOE 708 areconfigured during a design phase based on a field of view and/or aresolution of a camera that is to be tested utilizing the DOE 708. Forinstance, for a camera having a field of view of 30 degrees and aresolution of 2 degrees, the DOE 708 may be configured to split aprimary light beam (e.g., the same as or similar to light beam 712) into15 light beams (e.g., the same as or similar to light beams 722) tocover each 2-degree resolution interval from among the 30 degrees of thefield of view. A size of a primary light beam (e.g., the same as orsimilar to light beam 712) and/or a size of the multiple light beams(e.g., the same as or similar to light beams 722) into which the primarylight beam is split by the DOE 708, in another aspect, may be definedbased on a cross-sectional area of the DOE 708, such as by sizing theapertures (e.g., apertures 808 of FIG. 8 ) to utilize a maximal amountof cross-sectional area of a side (e.g., side 806 of FIG. 8 ) of the DOE708. In some examples, diffractive optical element 708 is furtherconfigured to project the light beams 722 through the lens and upon animage sensor of the camera, when optical axes of laser 702, beamexpanding lens 704, collimator 706, diffractive optical element 708, andcamera are mutually aligned, to enable the image sensor to capture animage of the light beams 722 for intrinsic calibration. In suchexamples, the diffractive optical element 708 may be further configuredto cause a grid of points to be formed on the image sensor of the camerabased on the projected light beams, with the grid of pointscorresponding to the view angles of the camera and enabling calculationof at least one intrinsic parameter (e.g., orientation of thediffractive optical element 708, focal length of the camera, principalpoint of the camera, distortion of the orientation of the camera). Insome embodiments, each point of the grid of points appears to originatefrom an infinite distance from the camera, to emulate a calibration“target” similar to a use case of cameras 202 a of autonomous vehicle102.

Referring now to FIGS. 8 and 9 , illustrated are diagrams 800 and 900 ofimplementations of diffractive optical elements (which, for example, maybe the same as, or similar to, diffractive optical element 708 or anyother diffractive optical element(s) described herein). In someembodiments, as shown in FIG. 8 , diffractive optical element 802includes a first surface 804 and a second side 806. The first surface804 includes apertures 808, which, in some embodiments, are arranged ina crosshair pattern. In one example, the apertures 808 are etched into aflat surface to form a mask on the first surface 804 of the diffractiveoptical element 802. In some examples, the diffractive optical element802 and the apertures 808 are circular, and diameters of the apertures808 decrease in a direction from an edge of the diffractive opticalelement 802 toward a center of the diffractive optical element 802. Withcontinued reference to FIG. 8 and FIG. 9 , in some examples, diffractiveoptical element 802 includes ridges 902 that are arranged in concentriccircles on the second surface 806 of the diffractive optical element802. In such examples, the apertures 808 are arranged along opticalpaths of the ridges 902.

Referring now to FIG. 10 , illustrated is a flowchart of a process 1000for manufacturing a geometric intrinsic camera calibration systemincluding a diffractive optical element. In some embodiments, one ormore of the steps described with respect to process 1000 are performed(e.g., completely, partially, and/or the like) by autonomous vehicle102, as above. Additionally or alternatively, in some embodiments one ormore steps described with respect to process 1000 may be performed(e.g., completely, partially, and/or the like) by another device orgroup of devices separate from or including autonomous vehicle 102, suchas a remote server (e.g., a remote server that is the same as or similarto remote AV system 114 and/or fleet management system 116 of FIG. 1 )carrying out some or all of the above calculations.

With continued reference to FIG. 10 , apertures are formed on a firstsurface of a diffractive optical element corresponding to a plurality ofview angles of a camera to be calibrated (block 1002). Processor 608 (orany other suitable processor) determines ridge angles based on the viewangles and based on a predetermined formula (e.g., Snell’s law) (block1004), as described in further detail in connection with FIG. 11 .Ridges are formed on a second surface of the diffractive optical elementbased on the ridge angles (block 1006). A collimator is arranged inbetween a laser and the diffractive optical element, with optical axesof the laser, the collimator, and the diffractive optical element beingmutually aligned (block 1008). Arranging the collimator in between thelaser and the diffractive optical element, in some examples, includesfixing a distance from the laser to the collimator and fixing a distancefrom the collimator to the diffractive optical element. In someexamples, a lens is arranged within the collimator and is configured toexpand a light beam output by the laser (block 1010).

Referring now to FIG. 11 , illustrated is a diagram 1100 of animplementation of a diffractive optical element 1102 (which, forexample, may be the same as, or similar to, diffractive optical element708 or any other diffractive optical element(s) described herein).Diffractive optical element 1102 includes a first surface 1104 (which,for example, may be the same as, or similar to, first surface 718 and/or804) and a second surface 1106 (which, for example, may be the same as,or similar to, second surface 720 and/or 806). FIG. 11 includes apartial cross-sectional view of a single ridge 1108 of diffractiveoptical element 1102 having a ridge angle 1116 (also referred to as aDOE surface angle), a view angle 1110, a theta1 1112, and a theta2 1114.In some embodiments, diffractive optical element 1102 includes multiple(e.g., 15) view angles, and multiple (e.g., 15) corresponding ridges(e.g., similar to ridge 1108). In such embodiments, the geometry (e.g.,angles) of each ridge is determined based on Snell’s law, a refractiveindex of material forming the diffractive optical element, and/or otherfactors, to achieve a desired field angle projection into a camera lensto be calibrated. For instance, the ridge angles (e.g., ridge angle1116), in some examples are determined by identifying the ridge anglesconfigured to deflect collimated beams from a collimator toward acamera-under-test at particular view angles (e.g., view angles 1110).According to one example, Snell’s law (reproduced herein as Equation(1)) and Equation (2) are utilized in an iterative manner, determiningvalues of theta2 (1114) based on successively inputted estimates oftheta1 (1112) until values of theta1 and theta2 that result in thedesired view angle (1110) are determined.

N1 × sin(theta1) = N2 × sin(theta2)

view angle = theta2 − (90^(∘) − theta1)

Once the values of theta1 and theta2 that result in the desired viewangle (1110) are determined, the respective ridge angle (1116) for thedesired view angle is determined according to Equation (3).

ridge angle = 90^(∘) − theta1

Table 1118 shows an example list of view angles 1110, correspondingvalues of N1 and N2 (refractive indices of material forming diffractiveoptical element 1102 and a vacuum, respectively), and values of theta11112, theta2 1114, and ridge angles 1116 that may be determined for anexample diffractive optical element 1102 having 15 view angles.

Referring now to FIG. 12 , illustrated is a flowchart of a process 1200for geometric intrinsic camera calibration using a diffractive opticalelement. In some embodiments, one or more of the steps described withrespect to process 1200 are performed (e.g., completely, partially,and/or the like) by autonomous vehicle 102, as above. Additionally oralternatively, in some embodiments one or more steps described withrespect to process 1200 may be performed (e.g., completely, partially,and/or the like) by another device or group of devices separate from orincluding autonomous vehicle 102, such as a remote server (e.g., aremote server that is the same as or similar to remote AV system 114and/or fleet management system 116 of FIG. 1 ) carrying out some or allof the above calculations.

With continued reference to FIG. 12 , a camera (e.g., camera 202 a) isarranged in front of a diffractive optical element (which, for example,may be the same as, or similar to, diffractive optical element 708 orany other diffractive optical element(s) described herein) with mutualalignment of optical axes (block 1202). Light beams are projected uponthe camera via the diffractive optical element in the manner describedelsewhere herein, and the camera captures one or more images based onthe projected light beams (block 1204). Processor 608 (or any suitableprocessor) receives at least one image captured by the camera based onthe light beams received from the diffractive optical element alignedwith the optical axis of the camera, the light beams having propagationdirections associated with view angles of the camera (block 1206). In anexample, the directions of the light beams include coordinates in acoordinate frame of the diffractive optical element. Processor 608identifies shapes in the image, for example, in the manner described infurther detail below in connection with FIG. 13 (block 1208). Processor608 determines a correspondence between the shapes in the image and thelight beams, for example, in the manner described in further detailbelow in connection with FIG. 13 . In one example, determining thecorrespondence between the shapes in the image and the light beamsincludes generating a list (e.g., pU1, DA1), (pU2, DA2), ..., (pUN, DAN)where the pUi represent pixel coordinates of dots in the image, and DAirepresent corresponding directions of the light beams in DOE-centriccoordinates. (block 1210). The pixel coordinates of the dots in theimage, for example, may be computed based on a centroid detectionalgorithm. (block 1212). Processor 608 stores in memory (e.g., memory612) a table that associates the pixel coordinates with the propagationdirections based on the determined correspondence between the shapes inthe image and the light beams. (block 1214). Processor 608 identifiesone or more intrinsic parameters of the camera (e.g., a focal length ofthe camera, a principal point of the camera, and/or a distortion of alens of the camera) that minimize a reprojection error function based onthe shapes in the image and the propagation directions (e.g., findingintrinsic parameters (Θ) and the rotation matrix CRD that minimize areprojection error function, such as the sum-of-squares reprojectionerror function shown in equation (4)) where ||.|| represents the 2-norm)(block 1216).

$Q\left( {\text{Θ}\text{,}_{C}R_{D}} \right) = {\sum\limits_{i = 1}^{N}\left\| {{}_{p}U_{i} - f\left( {{}_{C}R_{D} \cdot_{D}A_{i},\text{Θ}} \right)} \right\|^{2}}$

Referring now to FIG. 13 , illustrated is a flowchart of a furtherprocess 1300 for geometric intrinsic camera calibration using adiffractive optical element. In some embodiments, process 1300 is thesame as or similar to the processes of blocks 1208, 1210, and/or 1212described above in connection with FIG. 12 . In some embodiments, one ormore of the steps described with respect to process 1300 are performed(e.g., completely, partially, and/or the like) by autonomous vehicle102, as above. Additionally or alternatively, in some embodiments one ormore steps described with respect to process 1300 may be performed(e.g., completely, partially, and/or the like) by another device orgroup of devices separate from or including autonomous vehicle 102, suchas processor 608, a remote server (e.g., a remote server that is thesame as or similar to remote AV system 114 and/or fleet managementsystem 116 of FIG. 1 ) carrying out some or all of the abovecalculations.

With continued reference to FIG. 13 , processor 608 (or any suitableprocessor) loads an image, such as the image 1400 in FIG. 14 that wascaptured by a camera (e.g., camera 202 a) based on light beams projectedthereupon by way of a diffractive optical element (which, for example,may be the same as, or similar to, diffractive optical element 708 orany other diffractive optical element(s) described herein) (1302).Processor 608 de-mosaics the loaded image using any suitable de-mosaicalgorithm (1304). Processor 608 identifies shapes (e.g., blobs, dots,and/or centroids as shown in image 1500 of FIG. 15 ) in the de-mosaicedimage by executing a weighted centroid detection algorithm based on thede-mosaiced image (1306). Processor 608 designates one of the identifiedshapes (e.g., shape 1602 of FIG. 16 ) as corresponding to a centralshape 1602 from among the shapes in image 1500 (1308). Processor 608sorts the shapes of image 1500 into an order (e.g., in the row andcolumn order indexed based on the central shape 1602 shown in FIG. 17 )based at least in part on positions of the plurality of shapes withrespect to the central shape 1602 (1310). Processor 608 associates eachshape with a corresponding light beam from among the light beams basedat least in part on the order of the shapes (1312).

The DOE intrinsic calibration modules described with reference to FIGS.6-17 can be used to determine the intrinsic properties of the camerasystem both with and without a window installed. These intrinsicproperties can then be compared to determine the effects of boresightshift caused by the window. A transformation that corrects for theboresight sight can also be determined and applied to future imagescaptured with the window installed to correct for the boresight shift.

FIGS. 18A-18C are illustrative of an example process. With reference toFIG. 18A, a camera assembly 1802 can be installed in a housing 1804.Without a protective window installed, an intrinsic calibration can beperformed (for example, as described above with reference to FIGS. 6-17) to determine, for a grid of pixels, the direction that the pixelspoint. In FIG. 18A, the directions that the pixels point are representedin plot 1810 a, with pixels pointing from the plus sign to the square.

The size of the grid and how close the points of the grid should betogether (e.g., the pixel pitch) of the diffractive optical element(DOE) can be, in some embodiments, determined based on the opticalsystem (e.g., the camera) that is going to be calibrated. Factors of theoptical system that can be considered include: (a) The FOV of thecamera. In some embodiments it is desirable to cover the camera’s entirefield of view such that you see the DOE points encompassing the fullFOV; (b) The grid size can be based on how many points in a particularcamera’s FOV to successfully calibrate the system using the intrinsiccalibration algorithm. For example, a 15 by 15 grid might be enough fora smaller FOV of 30-40 degrees, but for a 90+ degree FOV camera, the15×15 grid might be spread apart too much to cover the entire FOV. Inthat case, it may be desirable to increase the grid size; (c) The pixelpitch. This can depend on the sensor resolution and/or FOV and thecalibration algorithm’s capability at hand. For example, if the camerahas high resolution, moderate FOV (e.g., about 50 degrees, and a robustcalibration algorithm is used, the pixel could be somewhere about 3-4microns provided the grids cover the entire FOV. In general, the morenumber of points cover the FOV, the more data points the calibrationalgorithm can utilize for its optimization, thereby providing moreaccurate algorithm provided sensor resolution doesn’t hinder it’sperformance.

As shown in FIG. 18B, a window 1806 can then be installed on the housing1804 over the camera assembly 1802. With the window 1806 installed, theintrinsic calibration can be performed again. For the grid of pixels,the directions are once again determined. These directions arerepresented by the plot 1810 b. As shown, by comparing plot 1810 a andplot 1801 b, the effects of the boresight shift can be seen in thedifferences between the plots. By computing the angular differencebetween each of the directions for each of the pixels, a transformationbetween the two can be obtained. When applied, the transformation cancorrect the boresight shift as shown in FIG. 18C. As shown, even withthe window 1806 installed, when the transformation is applied, plot 1810c appears similar or identical to the plot 1810 a which represents thesystem without the boresight shift caused by the window 1806.

FIGS. 19A and 19B illustrate the effect using a larger grid of pixels.FIG. 19A represents a plot of pixel directions obtained throughintrinsic calibration prior to installation of the window, and FIG. 19Billustrates a plot of pixel directions obtained through intrinsiccalibration after installation of the window. As shown, pixel directionshave changed in FIG. 19B. This change is caused by the boresight shift.By computing the angular difference between the pixel directions foreach pixel in the grid, the correcting transformation can be obtained.

FIG. 20 is a flowchart illustrating an example process 2000 fordetermining a transformation that can correct for boresight shift. Theprocess begins at block 2002 by mounting a camera assembly in a casingor housing without installation of a window over the camera assembly. Atblock 2004, the camera is calibrated without the window installed. Thecalibration can include the intrinsic calibration using a DOE intrinsiccalibration module as described above with reference to FIGS. 6-17 . Thecalibration can determine, for example, a pixel direction (e.g.,three-dimensional ray directions) for a plurality of points in a grid.The number of pixels and the size of the grid can be configured to coverthe field of view of the camera assembly. This information can be storedas calibration data C1.

Moving to block 2006, the window can then be installed over the cameraassembly. With the window installed, at block 2008, the camera iscalibrated for a second time. The calibration can include the intrinsiccalibration using a DOE intrinsic calibration module as described abovewith reference to FIGS. 6-17 . The calibration can determine, forexample, the pixel direction (e.g., three-dimensional ray directions)for the plurality of points in a grid. This information can be stored ascalibration data C2.

At block 2010, calibration data C1 (without the window) and calibrationdata C2 are compared to determine the angular difference between thepixel directions for each pixel in the grid. These differences arecaused by the boresight shift and can be used to determine atransformation that corrects to the boresight shift. In someembodiments, the transform is a comparison between the ray anglesbetween the ray directions of a particular point in the FOV with andwithout the styling window/optical layer. This ray angles differenceexists for every grid point in 3D space. In some embodiments, anextrinsic calibration between the two grid “planes” provides a rotationand translation matrix.

At block 2012, the transformation can be applied to each subsequentimages captured by the camera to correct for the boresight shift.

In the foregoing description, aspects and embodiments of the presentdisclosure have been described with reference to numerous specificdetails that can vary from implementation to implementation.Accordingly, the description and drawings are to be regarded in anillustrative rather than a restrictive sense. The sole and exclusiveindicator of the scope of the invention, and what is intended by theapplicants to be the scope of the invention, is the literal andequivalent scope of the set of claims that issue from this application,in the specific form in which such claims issue, including anysubsequent correction. Any definitions expressly set forth herein forterms contained in such claims shall govern the meaning of such terms asused in the claims. In addition, when we use the term “furthercomprising,” in the foregoing description or following claims, whatfollows this phrase can be an additional step or entity, or asub-step/sub-entity of a previously-recited step or entity.

Various additional example embodiments of the disclosure can bedescribed by the following clauses:

-   Clause 1: A method, comprising:    -   positioning a camera assembly in a housing, the camera assembly        comprising a lens assembly and an image sensor, the housing        positioned relative to a target such that the calibration target        at least partially covers a field of view of the camera        assembly;    -   based on a first output of the image sensor, determining a first        plurality of pixel locations corresponding to a plurality of        locations on the target;    -   based on a second output of the image sensor obtained with a        window positioned on the housing, determining a second plurality        of pixel locations corresponding to the plurality of locations        on the target, wherein a boresight shift caused by the window        causes the second plurality of pixel locations to differ from        the first plurality of pixel locations;    -   generating a transformation that maps the second plurality of        pixel locations to the first plurality of pixel locations; and    -   applying the transformation to subsequent images captured by the        camera assembly with the window installed over the camera        assembly.-   Clause 2: The method of Clause 1, wherein the transformation    corrects for the boresight shift caused by the window.-   Clause 3: The method of any of Clauses 1 or 2, wherein:    -   determining the first plurality of pixel locations corresponding        to the plurality of locations on the target comprises, for each        of the first plurality of pixel locations, determining a first        three-dimensional ray direction from the pixel location to the        corresponding location on the target; and    -   determining the second plurality of pixel locations        corresponding to the plurality of locations on the target        comprises, for each of the second plurality of pixel locations,        determining a second three-dimensional ray direction from the        pixel location to the corresponding location on the target.-   Clause 4: The method of Clause 3, wherein generating the    transformation comprises determining an angular difference between    each of the first and second three-dimensional ray directions.-   Clause 5: The method of any of Clauses 1-4, wherein the target    comprises a grid of points.-   Clause 6: The method of any of Clauses 1-5, wherein the housing is    positioned relative to the target such that the target fully covers    the field of view of the camera sensor.-   Clause 7: The method of any of Clauses 1-6, further comprising    storing the transformation.-   Clause 8: At least one non-transitory storage media storing    instructions that, when executed by at least one processor, cause    the at least one processor to:    -   determine, based on a first output of a camera assembly, a first        plurality of pixel locations corresponding to a plurality of        locations on a target, wherein the first output of the camera        assembly is obtained prior to positioning a window over the        camera assembly;    -   determine, based on a second output of the camera assembly        obtained with the window positioned over the camera assembly, a        second plurality of pixel locations corresponding to the        plurality of locations on the target;    -   generate a transformation that maps the second plurality of        pixel locations to the first plurality of pixel locations; and    -   store the transformation in a memory associated with the camera        assembly such that the transformation is applied to subsequent        images captured by the camera assembly with the window installed        over the camera assembly.-   Clause 9: The at least one non-transitory storage media of Clause 8,    wherein the transformation corrects for the boresight shift caused    by the window.-   Clause 10: The at least one non-transitory storage media of any of    Clauses 8 or 9, wherein the instructions further cause the at least    one processor to:    -   determine the first plurality of pixel locations corresponding        to the plurality of locations on the target by, for each of the        first plurality of pixel locations, determining a first        three-dimensional ray direction from the pixel location to the        corresponding location on the target; and    -   determine the second plurality of pixel locations corresponding        to the plurality of locations on the target by, for each of the        second plurality of pixel locations, determining a second        three-dimensional ray direction from the pixel location to the        corresponding location on the target.-   Clause 11: The at least one non-transitory storage media of Clause    10, wherein generating the transformation comprises determining an    angular difference between each of the first and second    three-dimensional ray directions.-   Claus 12: The at least one non-transitory storage media of any of    Clauses 8-11, wherein the target comprises a grid of points.-   Clause 13: The at least one non-transitory storage media of any of    Claims 8-12, wherein the instructions further cause the at least one    processor to store the transformation.-   Clause 14: A system, comprising:    -   a camera assembly comprising a lens assembly and an image sensor        positioned within a housing;    -   a computer readable medium storing a transformation that        corrects for a boresight shift caused by the window, wherein the        transformation is generated by:        -   determining, based on a first output of the camera assembly,            a first plurality of pixel locations corresponding to a            plurality of locations on a target, wherein the first output            of the camera assembly is obtained prior to positioning a            window over the camera assembly,        -   determining, based on a second output of the camera assembly            obtained with the window positioned over the camera            assembly, a second plurality of pixel locations            corresponding to the plurality of locations on the target,            and        -   mapping the second plurality of pixel locations to the first            plurality of pixel locations; and    -   a processor configured to apply the transformation to images        captured by the camera assembly.-   Clause 15: The system of Clause 14, wherein:    -   determining the first plurality of pixel locations corresponding        to the plurality of locations on the target comprises, for each        of the first plurality of pixel locations, determining a first        three-dimensional ray direction from the pixel location to the        corresponding location on the target; and    -   determining the second plurality of pixel locations        corresponding to the plurality of locations on the target        comprises, for each of the second plurality of pixel locations,        determining a second three-dimensional ray direction from the        pixel location to the corresponding location on the target.-   Clause 16: The system of Clause 15, wherein the transformation is    generated by determining an angular difference between each of the    first and second three-dimensional ray directions.-   Clause 17: The system of any of Clauses 14-16, wherein the target    comprises a grid of points.-   Clause 18: The system of any of Clauses 14-17, wherein the window is    a protective window.-   Clause 19: The system of any of Clauses 14-18, wherein the window    seals the camera assembly.-   Clause 20: The system of any of Clauses 14-19, wherein the housing    is positioned on an autonomous system of a vehicle.

What is claimed is:
 1. A method, comprising: positioning a cameraassembly in a housing, the camera assembly comprising a lens assemblyand an image sensor, the housing positioned relative to a target suchthat the calibration target at least partially covers a field of view ofthe camera assembly; based on a first output of the image sensor,determining a first plurality of pixel locations corresponding to aplurality of locations on the target; based on a second output of theimage sensor obtained with a window positioned on the housing,determining a second plurality of pixel locations corresponding to theplurality of locations on the target, wherein a boresight shift causedby the window causes the second plurality of pixel locations to differfrom the first plurality of pixel locations; generating a transformationthat maps the second plurality of pixel locations to the first pluralityof pixel locations; and applying the transformation to subsequent imagescaptured by the camera assembly with the window installed over thecamera assembly.
 2. The method of claim 1, wherein the transformationcorrects for the boresight shift caused by the window.
 3. The method ofclaim 1, wherein: determining the first plurality of pixel locationscorresponding to the plurality of locations on the target comprises, foreach of the first plurality of pixel locations, determining a firstthree-dimensional ray direction from the pixel location to thecorresponding location on the target; and determining the secondplurality of pixel locations corresponding to the plurality of locationson the target comprises, for each of the second plurality of pixellocations, determining a second three-dimensional ray direction from thepixel location to the corresponding location on the target.
 4. Themethod of claim 3, wherein generating the transformation comprisesdetermining an angular difference between each of the first and secondthree-dimensional ray directions.
 5. The method of claim 4, wherein thetarget comprises a grid of points.
 6. The method claim 1, wherein thehousing is positioned relative to the target such that the target fullycovers the field of view of the camera sensor.
 7. The method of claim 1,further comprising storing the transformation.
 8. At least onenon-transitory storage media storing instructions that, when executed byat least one processor, cause the at least one processor to: determine,based on a first output of a camera assembly, a first plurality of pixellocations corresponding to a plurality of locations on a target, whereinthe first output of the camera assembly is obtained prior to positioninga window over the camera assembly; determine, based on a second outputof the camera assembly obtained with the window positioned over thecamera assembly, a second plurality of pixel locations corresponding tothe plurality of locations on the target; generate a transformation thatmaps the second plurality of pixel locations to the first plurality ofpixel locations; and store the transformation in a memory associatedwith the camera assembly such that the transformation is applied tosubsequent images captured by the camera assembly with the windowinstalled over the camera assembly.
 9. The at least one non-transitorystorage media of claim 8, wherein the transformation corrects for theboresight shift caused by the window.
 10. The at least onenon-transitory storage media of claim 8, wherein the instructionsfurther cause the at least one processor to: determine the firstplurality of pixel locations corresponding to the plurality of locationson the target by, for each of the first plurality of pixel locations,determining a first three-dimensional ray direction from the pixellocation to the corresponding location on the target; and determine thesecond plurality of pixel locations corresponding to the plurality oflocations on the target by, for each of the second plurality of pixellocations, determining a second three-dimensional ray direction from thepixel location to the corresponding location on the target.
 11. The atleast one non-transitory storage media of claim 10, wherein generatingthe transformation comprises determining an angular difference betweeneach of the first and second three-dimensional ray directions.
 12. Theat least one non-transitory storage media of claim 8, wherein the targetcomprises a grid of points.
 13. The at least one non-transitory storagemedia of claim 8, wherein the instructions further cause the at leastone processor to store the transformation.
 14. A system, comprising: acamera assembly comprising a lens assembly and an image sensorpositioned within a housing; a computer readable medium storing atransformation that corrects for a boresight shift caused by the window,wherein the transformation is generated by: determining, based on afirst output of the camera assembly, a first plurality of pixellocations corresponding to a plurality of locations on a target, whereinthe first output of the camera assembly is obtained prior to positioninga window over the camera assembly, determining, based on a second outputof the camera assembly obtained with the window positioned over thecamera assembly, a second plurality of pixel locations corresponding tothe plurality of locations on the target, and mapping the secondplurality of pixel locations to the first plurality of pixel locations;and a processor configured to apply the transformation to imagescaptured by the camera assembly.
 15. The system of claim 14, wherein:determining the first plurality of pixel locations corresponding to theplurality of locations on the target comprises, for each of the firstplurality of pixel locations, determining a first three-dimensional raydirection from the pixel location to the corresponding location on thetarget; and determining the second plurality of pixel locationscorresponding to the plurality of locations on the target comprises, foreach of the second plurality of pixel locations, determining a secondthree-dimensional ray direction from the pixel location to thecorresponding location on the target.
 16. The system of claim 15,wherein the transformation is generated by determining an angulardifference between each of the first and second three-dimensional raydirections.
 17. The system of claim 14, wherein the target comprises agrid of points.
 18. The system of claim 14, wherein the window is aprotective window.
 19. The system of claim 14, wherein the window sealsthe camera assembly.
 20. The system of claim 14, wherein the housing ispositioned on an autonomous system of a vehicle.